Communication systems seek to communicate as much information as possible in as little time as possible using as little power as possible and over as small of a bandwidth as possible. A wide variety of data compression, error correction, and modulation techniques have been developed to further this goal.
Data compression re-characterizes an original data set using less data than was included in the original data set but in a manner that allows as much accuracy as possible in reconstruction of the original data. Data compression is often employed on human-perceivable data, such as video, imagery, or audio, that typically include a large amount of redundant content which the compression removes and which need not be perfectly reconstructed. If the original data set represents video, imagery, or audio, tremendous amounts of compression can be achieved while still having the reconstructed video, image, or audio be readily perceivable. Other types of data sets, such as computer data, may also be reduced by compression. But compression algorithms that insure a perfect reconstruction are typically employed with such data sets. A lesser, but still significant, amount of compression can often be achieved.
Compression and reconstruction are highly desirable in communication systems because a much smaller quantity of compressed data needs to be transmitted through a communication channel than would be required to transmit the original data set. But a problem with compressed data is that it can become more vulnerable to communication errors.
Error-correction encoding, hereinafter referred to as error-correction (EC) coding, typically involves convoluting communicated data and embedding redundant information so that a receiver can correct the transmission even if errors occur. EC coding requires a greater quantity of data to be communicated through a channel than would be required if EC coding were omitted. To this extent, EC coding is undesirable and works at cross purposes to compression. But relatively small amounts of EC coding introduce coding gain that can more than offset the cost of transmitting additional redundant data. In general, EC coding maintains at least a minimum bit error rate while channel conditions deteriorate. However, when channel conditions deteriorate to some point, the coding utterly fails and massive increases in bit errors pass through an EC decoder. Generally, greater amounts of embedded redundant information lead to higher quality received data because more information is available with which to detect and correct errors.
Modulation refers to applying to-be-communicated data, whether or not compressed and/or EC coded, to signals which are then imposed on a physical channel (e.g., RF, cable, optical) through which the data are to be communicated. These signals are configured in power and bandwidth to accommodate the attributes and requirements of the physical channel. Moreover, modulation formats, such as CDMA, M-QAM and the like and rates delivered thereby are also configured to match the physical channel.
Conventional modulators manipulate power and rate to achieve a desired quality of signal. Typically, at a given quality of signal and for a given channel, an increase in power will permit communication of data at a greater rate or a decrease in rate will permit the use of less power. Likewise, at a given power for a given channel, an increase in rate dictates a decrease in quality, or a decrease in rate permits an increase in quality. Or, at a given rate for a given channel, an increase in power permits an increase in quality, or a decrease in power dictates a decrease in quality.
FIG. 1 shows a block diagram of a generic conventional communication system that employs compression, EC coding, and modulation. At an innermost level, a modulator (mod) 100 and a demodulator (demod) 102 perform complementary operations with respect to a physical channel 104. The characteristics of physical channel 104 influence the quality at which data may be conveyed. The modulator 100, demodulator 102, and physical channel 104 together provide a logical intermediate channel 106 with conveyance quality characteristics that may have been transformed from those of physical channel 104. Typically, modulator 100 is configured so that logical intermediate channel 106 appears to convey data at a fixed signal quality, with power and rate being adjusted as needed to accomplish the prescribed signal quality. An EC coding block 108 and an EC decoding block 110 perform complementary operations with respect to logical intermediate channel 106. Typically, EC coding block 108 is configured to implement an encoding scheme for the prescribed quality presented to it by logical intermediate channel 106 and so that a much improved signal quality is presented through a logical outer channel 112. A compression block 114 and a decompression block 116 are then configured to operate in an environment where their output is passed through the logical outer channel 112 at this much improved signal quality.
In some robust video and image coding schemes, the compression and EC coding functions are integrated or jointly matched to the fixed quality channel presented to them by logical intermediate channel 106. The result is typically an improvement in efficiency in combination with improvements in the way degradation occurs as errors increase.
FIG. 2 depicts relationships between different coding schemes, received quality of source information communicated through a channel, and channel quality, assuming other factors remain constant. Generally, a good quality channel allows a weak coding scheme to embed less redundant information with the source data and therefore achieve a higher source data rate than would be achieved using a strong coding scheme. Referring back to FIG. 1, EC coding block 108, or EC coding block 108 jointly matched with compression block 114, should implement the single EC coding scheme that achieves the highest received quality and rate for the channel quality presented to it by logical intermediate channel 106.
While the conventional approach discussed above works well for narrowband channels, problems result when this approach is applied in wideband channels, such as those often used in connection with multi-carrier (MC) modulation, multi-tone modulation, OFDM, DSL, and the like. FIG. 3 depicts two examples of the complex channel gain possible in a wideband physical channel 104 without any transmission from modulator 100. In FIG. 3, the solid line represents frequency-selective fading, and the dotted line represents an interfering or jamming signal. Different ones of the subchannels that make up wideband physical channel 102 have different abilities to convey data due to this channel gain. Conventional techniques call for modulating data into each subchannel so that each subchannel delivers data at substantially the same quality as the other subchannels.
Unfortunately, this conventional technique uses resources inefficiently. Transforming low quality subchannels that have low channel-gain-to-noise ratios (CGNRs) into medium quality data conveyors requires the expenditure of excessive amounts of power or a costly decrease in source rate. And, transforming high quality subchannels that have high CGNRs into only medium quality data conveyors saves little power or produces little rate improvement. Moreover, the transforming of a range of conveyance quality demonstrated by a wideband physical channel 104 into a single-conveyance-quality logical intermediate channel 106 causes coding to be applied inefficiently. The variation in quality of subchannels within physical channel 104 is not corrected, but merely transformed to a constant, at logical intermediate channel 106. As demonstrated by the shaded area in FIG. 2, higher received quality, and often a higher source rate, result from using a variety of coding schemes when facing a range of conveyance qualities when compared to using a single encoding scheme.